Rough concept analysis: a synthesis of rough sets and formal concept analysis
Fundamenta Informaticae - Special issue: rough sets
Algebraic aspects of attribute dependencies in information systems
Fundamenta Informaticae
Formal Concept Analysis: Mathematical Foundations
Formal Concept Analysis: Mathematical Foundations
Rough Sets and Concept Lattices
RSKD '93 Proceedings of the International Workshop on Rough Sets and Knowledge Discovery: Rough Sets, Fuzzy Sets and Knowledge Discovery
RSFDGrC '99 Proceedings of the 7th International Workshop on New Directions in Rough Sets, Data Mining, and Granular-Soft Computing
Concept Data Analysis: Theory and Applications
Concept Data Analysis: Theory and Applications
Relations of attribute reduction between object and property oriented concept lattices
Knowledge-Based Systems
A novel approach to attribute reduction in concept lattices
RSKT'06 Proceedings of the First international conference on Rough Sets and Knowledge Technology
Attribute reduction in concept lattice based on discernibility matrix
RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part II
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As one of the important problems of knowledge discovery and data analysis, knowledge reduction can make the discovery of implicit knowledge in data easier and the representation simpler. In this paper, a new approach to knowledge reduction in concept lattices is developed based on irreducible elements, and characteristics of attributes and objects are also analyzed. Furthermore, algorithms for finding attribute and object reducts are provided respectively. The algorithm analysis shows that the approach to knowledge reduction involves less computation and is more tractable compared with the current methods.